| ProcessingInput | R Documentation |
Accepts parameters that specify an Amazon S3 input for a processing job and provides a method to turn those parameters into a dictionary.
new()Initializes a “ProcessingInput“ instance. “ProcessingInput“ accepts parameters that specify an Amazon S3 input for a processing job and provides a method to turn those parameters into a dictionary.
ProcessingInput$new(
source = NULL,
destination = NULL,
input_name = NULL,
s3_data_type = c("S3Prefix", "ManifestFile"),
s3_input_mode = c("File", "Pipe"),
s3_data_distribution_type = c("FullyReplicated", "ShardedByS3Key"),
s3_compression_type = c("None", "Gzip"),
s3_input = NULL,
dataset_definition = NULL,
app_managed = FALSE
)source(str): The source for the input. If a local path is provided, it will automatically be uploaded to S3 under: "s3://<default-bucket-name>/<job-name>/input/<input-name>".
destination(str): The destination of the input.
input_name(str): The name for the input. If a name is not provided, one will be generated (eg. "input-1").
s3_data_type(str): Valid options are "ManifestFile" or "S3Prefix".
s3_input_mode(str): Valid options are "Pipe" or "File".
s3_data_distribution_type(str): Valid options are "FullyReplicated" or "ShardedByS3Key".
s3_compression_type(str): Valid options are "None" or "Gzip".
s3_input(:class:'~sagemaker.dataset_definition.S3Input') Metadata of data objects stored in S3
dataset_definition(:class:'~sagemaker.dataset_definition.DatasetDefinition') DatasetDefinition input
app_managed(bool): Whether the input are managed by SageMaker or application
to_request_list()Generates a request dictionary using the parameters provided to the class.
ProcessingInput$to_request_list()
format()format class
ProcessingInput$format()
clone()The objects of this class are cloneable with this method.
ProcessingInput$clone(deep = FALSE)
deepWhether to make a deep clone.
Other Processor:
ProcessingJob,
ProcessingOutput,
Processor,
ScriptProcessor
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